As a biometric is a biological characteristic (such as a fingerprint, the geometry of a hand, retina pattern, iris texture, etc.) of an individual, biometric techniques can be used as an additional verification factor since biometrics are usually more difficult to obtain than other non-biometric credentials. Biometrics can be used for identification and/or authentication (also referred to as identity assertion and/or verification).
Biometric identity assertion can require a certain level of security as dictated by the application. For example, authentication in connection with a financial transaction or gaining access to a secure location requires higher security levels. As a result, preferably, the accuracy of the biometric representation of a user is sufficient to ensure that the user is accurately authenticated and security is maintained.
Moreover, missing, swapping, mixing, and illegal adoption of newborns is a global challenge and using automated biometric systems has been proposed to identify new borns based on their face, iris, fingerprint, footprint, and/or palmprint.
However, to the extent iris, face, finger, and voice identity assertion systems exist and provide the requisite level of accuracy, such systems require dedicated devices and applications and are not easily implemented on conventional smartphones, which have limited camera resolution and light emitting capabilities.
Electronic fingerprint sensors have already been added to smartphone devices, the iPhone 6 smartphone by Apple Inc. of Cupertino Calif. and the Samsung S5 smartphone by Samsung Co. of Samsung Korea are examples of this. In these devices, the user must enroll their fingerprint data by placing their finger on the sensor, at a later date the user may verify their identity by repositioning their finger on the sensor, the fingerprint data is compared with the enrollment data and if it matches the identity of the user is confirmed. Should the fingerprint not match then the user can be identified as an imposter. A disadvantage of these systems is that the fingerprint sensor adds size weight and cost to the device. Furthermore, for these reasons it is advantageous to minimize the size of the fingerprint sensor, and as such the fingerprint sensor typically captures only a portion of the fingerprint which reduces the effectiveness of the identification. The smaller the region of capture for the fingerprint sensor, the more chance there is that another finger will match by chance, and the more likely that any error in the fingerprint data will cause a false rejection of the authentic user.
Moreover, Capturing newborns' fingerprints by using the traditional fingerprint sensors is challenging because of the the size of the finger and the difficulty of holding the newborn hand and placing it on the sensor.
In practical terms this means that the users (i.e., adults and newborns) suffer a higher level of inconvenience from false rejections, and the application of the sensor is limited to non-critical usage such as low value payments. Fingerprint sensors may also be subject of spoof attacks, where for example a mold of the authentic users fingerprint is placed in the fingerprint sensor to enable an imposter to pass authentication. This provides a further reason to restrict usage to non-critical applications.
A further challenge is that only a few mobile devices are equipped with fingerprint sensors which limits the numbers of people who have access to fingerprint authorization systems, and causes an inconsistency in authentication method between devices.
Systems have been proposed that analysis the image of a single finger using the camera of a mobile device, these systems are potentially more convenient, however, the lowest false accept rates and false reject rates for such systems for imaging and analyzing a single finger are still not reliable enough for applications requiring higher security such as medium to high value purchases and enterprises systems (i.e., large scale systems).
As such there is a need for a more reliable, and more ubiquitous finger recognition system.